(iii) Self-Attention Module with Residual Connection: In the proposed \(\text{TC-HGR}\)  architecture, we used the “Temporal Convolution Block” along with the “Attention” mechanism. In [1]}, the authors showed that the attention mechanism allows a model to present important information in a given input sequence. Moreover, the attention mechanism has recently been used [2]} in the context of sEMG-based hand gesture recognition, where experiments have demonstrated the ability of attention to identifying specific pieces of information in the sequential nature of the sEMG signals. On the other hand, in References [3]}, [4]}, it was shown that temporal convolutions and attention are complementary mechanisms, i.e., the former captures a long history while the latter identifies a specific type of information.
